CraftR Project

whitePaper | December 21, 2022

The evolution of cloud-based technology is continuing to reshape the data management landscape. As data volumes increase, users in different industries are demanding flexible, scalable processes that enable them to leverage a wider variety of sources, uncover new insights and confidently make decisions that will drive their businesses forward.

whitePaper | March 3, 2023

In today’s world, data is king and has become a major source of competitive differentiation for businesses across all industries. The COVID-19 pandemic has further accelerated the use and importance of data as the world’s governments and businesses adapted.

whitePaper | February 7, 2020

Multiple studies have proven that, while the business demand for databases grows, operational teams are constrained by traditional, reactive processes. Combined with budgetary pressures, this causes them to fall short in meeting the demand in a timely fashion. In addition, as companies adopt cloud paradigms, operational teams must manage across on-premises and cloud environments with the same resources. To be effective, companies need to shift from a reactive posture to one of standardization and proactive analysis and planning by leveraging intuitive tooling to automate manually intensive and non-value adding activities and to deliver real-time insights.

whitePaper | May 18, 2021

Next-gen data operations require next-gen data technologies and strategies and Azure is an ideal platform for this modernization to take place. Download this white paper to better understand the strategies, philosophies, and technologies your organization needs to expand analytics abilities, reduce technical debt, embrace AI, and more.

whitePaper | January 31, 2020

Many companies have invested heavily in specialized enterprise data warehouses (EDW) and Extract, Transform and Load (ETL) technologies to analyze their operational data. But these technologies were never designed to be truly real-time.They were originally built for batch, and that original design limits how real-timeEDWs and ETL can become. They were also designed to support a focused group ofanalysts, not a larger group of employees spanning operational functions, or even partner and end customers.

whitePaper | October 1, 2021

centering your database and data analytics workload development and deployment on a Kubernetes-based container, you can create a more efficient and speedy data life cycle. Access this white paper to learn how to improve key capabilities for database and data analytics workloads across hybrid cloud environments.